Biomedical subjects

Kristian Wennmalm

Publications and source records attributed to Kristian Wennmalm.

3 recordsLinked to original sources

PubMed2007

Gene expression in 16q is associated with survival and differs between Sørlie breast cancer subtypes.

We have investigated the relationship between gene expression and chromosomal positions in 402 breast cancer patients. Using an overrepresentation approach based on Fisher's exact test, we identified disproportionate contributions of specific chromosomal positions to genes associated with survival. Our major finding is that the gene expression in the long arm of chromosome 16 stands out in its relationship to survival. This arm contributes 36 (18%) and 55 (11%) genes to lists negatively associated with recurrence-free survival (set to sizes 200 and 500). This is a highly disproportionate contribution from the 313 (2%) genes in this arm represented on the used Affymetrix U133A and B microarray platforms (Bonferroni corrected Fisher test: P < 2.2 x 10(-16)). We also demonstrate differential expression in 16q across tumor subtypes, which suggests that the ERBB2, basal, and luminal B tumors progress along a high grade-poor prognosis path, while luminal A and normal-like tumors progress along a low grade-good prognosis path, in accordance with a previously proposed model of tumor progression. We conclude that important biological information can be extracted from gene expression data in breast cancer by studying non-random connections between chromosomal positions and gene expression. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

Breast Neoplasms↗

PubMed2006

Comparative microarray analysis.

Microarrays enable high-throughput parallel gene expression analysis, and their use has grown exponentially during the past decade. We are now in a position where individual experiments could benefit from using the swelling public data repositories to allow microarrays to progress from being a hypothesis-generating tool to a powerful resource that can be used to test hypothesis about biology. Comparative microarray analysis could better distinguish phenotypes from associated phenotypes; identify valid differentially expressed genes by combining many studies; test new hypothesis; and discover fundamental patterns of gene regulation. This review aims to describe the additional methodology needed for such comparative microarray analysis, and we identify and discuss a number of problems such as loss of published data, lack of annotations, and variable array quality, which need to be solved before comparative microarray analysis can be used in a more systematic and powerful manner.

Animals↗

PubMed2005

The expression signature of in vitro senescence resembles mouse but not human aging.

BACKGROUND: The biological mechanisms that underlie aging have not yet been fully identified. Senescence, a phenomenon occurring in vitro, limits the number of cell divisions in mammalian cell cultures and has been suggested to contribute to aging. RESULTS: We investigated whether the changes in gene expression that occur during mammalian aging and induction of cellular senescence are similar. We compared changes of gene expression in seven microarray datasets from aging human, mouse and rat, as well as four microarray datasets from senescent cells of man and mouse. The datasets were publicly available or obtained from other laboratories. Correlation measures were used to establish similarities of the expression profiles and gene ontology analyses to identify functional groups of genes that are co-regulated. Robust similarities were established between aging in different species and tissues, indicating that there is an aging transcriptome. Although some cross-species comparisons displayed high correlation, intra-species similarities were more reliable. Similarly, a senescence transcriptome was demonstrated that is conserved across cell types. A similarity between the expression signatures of cellular senescence and aging could be established in mouse, but not in human. CONCLUSION: Our study is the first to use microarray data from several studies and laboratories for dissection of a complex biological phenotype. We demonstrate the presence of a mammalian aging transcriptome, and discuss why similarity between cellular senescence and aging is apparent in aging mice only.

Aging↗